Transformer-Assisted LLM-Based Source Code Summarisation: to Enable More Secure Software Development
Neural Source Code Summarisation (NSCS) aims to generate natural language summaries of source code to improve developers' and maintainers' understanding of code. Source code summaries are vital during the maintenance phase of the Secure Software Development Lifecycle (SSDLC), as they improve maintainers' understanding of code and help reduce the number of bugs and vulnerabilities in a software system. However, summaries are often missing, incomplete, or outdated in many software systems. Solutions to this problem use small, task-specific Transformer models or code-aware Large Language Models (LLMs). Task-specific Transformer-generated summaries often score well across many natural languag...
| Authors | Jesse Phillips, Tracy Hall, Paul Rayson et al. |
|---|---|
| Primary category | cs.SE |
| Published | 23 July 2026 |
| Last updated at source | 23 July 2026 |
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